Owner, Computer Scientist, Electrical & Computer Engineering of JonesAI, LLC

PhD computer science, MS and BS electrical engineering, AAS electronics, with honors I have over 36 years of R&D experience in computer science and engineering. I'm passionate about the theory and application of probabilistic graph models, Bayesian machine learning methods, neural networks, and deep learning. Other research interests and expertise include dataflow graphs, queuing networks, Petri nets, hierarchical Bayesian networks, Markov chains, hierarchical mixture models, hidden Markov models, and Kalman filters. I have a US Patent (8504493 B2) entitled "Self-organizing Sequential Memory Pattern Machine and Reinforcement Learning Method" that combines semi-supervised and reinforcement learning with a Bayesian treatment of hierarchical models to learn and reason about probability distributions of distributions. I like to code software in Python, Julia, R, C, C++, Scala, JacaScript, and Rust. I am adept in CUDA-capable GPU computing for HPC and stochastic optimization of deep learning networks. Skillset: Machine learning • pattern recognition • artificial intelligence • graph models • graph processing • statistical data modeling • probability theory & practice • stochastic process models • statistical signal processing • Bayesian networks • Markov networks • Markov chains • Markov logic networks • MCMC methods • Variational Bayes methods • ensemble methods • stochastic optimization • neural networks • deep learning • reinforcement learning • GFlowNets • knowledge-gradient optimal learning • semi-supervised learning • recurrent neural network learning (expert with LSTM and GRU) • time-series prediction • symbolic dynamic analysis • anomaly detection • PyMC3 • Spark • ND4J/S • Deeplearning4j • Matlab • VHDL • SystemC • OpenCL • algorithm design, analysis & optimization • queuing networks • dataflow graph model of computation • discrete-event simulation development • multiprocessing system development • wireless sensor networks • Industrial IoT • network protocol technologies • telemetry data transport • space technology • lidar imaging (3D) data processing • lidar altimetry (airborne & spaceborne) • image processing • everything Python • PyTorch • Torch • MXNet • TensorFlow • Keras • Julia • Flux.jl • Turing.jl • Caffe • Scikit-learn • NumPy • SciPy • very experienced with decision trees, random forest & XGBoost • latent topic modeling • NLTK • spaCy • fastText • adept at AWS EC2, SageMaker, S3, Redshift, Athena • MS Azure • GCP • PostgreSQL • MySQL • NoSQL • Neo4j • ArangoDB • Memgraph Senior Member IEEE, IEEE Computer Society